An introduction to the use of AI in cardiology
A review of the current state of AI in cardiology and a speculation of its future potential
A review of the current state of AI in cardiology and a speculation of its future potential
This is part of a larger conversation between, Dr Nay Aung, Dr Steffen Petersen and Dr Alborz Amir-Khalili.
Driven by our partnership with clinicians, we are proud to introduce the next evolution of the CardioCare program, designed to have a profound effect on hospitals, health systems and patients
Dr. John S. Rumsfeld, Chief Innovation Officer, American College of Cardiology provides crucial advice and insights for fellow cardiologists
A review of the top 3 AI in cardiology papers of the past year. 1. Zimmerman A et al. Usefulness of Machine Learning in COVID-19 for the Detection and Prognosis of Cardiovascular Complications.Review in Cardiovascular Medicine 2020. Machine learning can be used to assess massive quantities o
1. Artificial intelligence in cardiology is more than using deep learning for cardiovascular imaging interpretation and can be extended into wearable technology (edge AI), administrative tasks (robotic process automation), and decision making (recurrent neural network for time series data). 2. In wo
One of the sessions at the AIMed Cardiology virtual conference took place yesterday (4 November) was on real-time applications of artificial intelligence (AI)
Electrocardiogram (ECG) was invented in 1895 and it has not changed much over the years, including the way results are being reported and printed out from the machine
Cardiology is no stranger to artificial intelligence (AI). It’s getting more common to deploy machine learning to interpret electrocardiograms (ECGs) for its potential to assist physicians during invasive electrophysiology procedures